Scheduling Under Fuzziness


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Scheduling Under Fuzziness


Scheduling Under Fuzziness

Author: Roman Slowiński

language: en

Publisher: Physica

Release Date: 2000


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This volume prepared by Roman Slowinski and Maciej Hapke is welcome because it is representative of the current state of the art in fuzzy set-based scheduling. Its publication proves that some operational research scientists start to consider fuzzy sets seriously as a bridge for a reconciliation between mathematical modeling and human scheduling practice. A difficulty for the reader of the fuzzy set scheduling literature is to understand the precise role of fuzzy sets in the various published papers. More often than not, the meaning of fuzzy sets remain unclear or must be guessed from the context of the problem. A major contribution of this volume is to try and clarify this issue through a suitable ordering of the papers, telling apart those where fuzzy sets is mainly a matter of representing preference, and those where the problem is one of scheduling under uncertainty. Taken from the foreword by Didier Dubois and Henry Prade

Production Engineering and Management under Fuzziness


Production Engineering and Management under Fuzziness

Author: Cengiz Kahraman

language: en

Publisher: Springer

Release Date: 2010-05-18


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Production engineering and management involve a series of planning and control activities in a production system. A production system can be as small as a shop with only one machine or as big as a global operation including many manufacturing plants, distribution centers, and retail locations in multiple continents. The product of a production system can also vary in complexity based on the material used, technology employed, etc. Every product, whether a pencil or an airplane, is produced in a system which depends on good management to be successful. Production management has been at the center of industrial engineering and management science disciplines since the industrial revolution. The tools and techniques of production management have been so successful that they have been adopted to various service industries, as well. The book is intended to be a valuable resource to undergraduate and graduate students interested in the applications of production management under fuzziness. The chapters represent all areas of production management and are organized to reflect the natural order of production management tasks. In all chapters, special attention is given to applicability and wherever possible, numerical examples are presented. While the reader is expected to have a fairly good understanding of the fuzzy logic, the book provides the necessary notation and preliminary knowledge needed in each chapter.

Fuzzy Systems and Soft Computing in Nuclear Engineering


Fuzzy Systems and Soft Computing in Nuclear Engineering

Author: Da Ruan

language: en

Publisher: Physica

Release Date: 2013-11-21


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Fuzzy systems and soft computing are new computing techniques that are tolerant to imprecision, uncertainty and partial truths. Applications of these techniques in nuclear engineering present a tremendous challenge due to its strict nuclear safety regulation. The fields of nuclear engineering, fuzzy systems and soft computing have nevertheless matured considerably during the last decade. This book presents new application potentials for Fuzzy Systems and Soft Computing in Nuclear Engineering. The root of this book can be traced back to the series of the first, second and third international workshops on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FUNS), which were successfully held in Mol, September 14-16, 1994 (FLINS'94), in Mol, September 25-27, 1996 (FLINS'96), and in Antwerp, September 14-16, 1998 (FLINS'98). The conferences were organised by the Belgian Nuclear Research Centre (SCKeCEN) and aimed at bringing together scientists, researchers, and engineers from academia and industry, at introducing the principles of fuzzy logic, neural networks, genetic algorithms and other soft computing methodologies, to the field of nuclear engineering, and at applying these techniques to complex problem solving within nuclear industry and related research fields. This book, as its title suggests, consists of nuclear engineering applications of fuzzy systems (Chapters 1-10) and soft computing (Chapters 11-21). Nine pertinent chapters are based on the extended version of papers at FLINS'98 and the other 12 chapters are original contributions with up-to-date coverage of fuzzy and soft computing applications by leading researchers written exclusively for this book.